Abstract

Estimating evapotranspiration is crucial for understanding Earth’s energy and water budget, ecosystem dynamics, and for improved water resource management. The Evapotranspiration Index (ET_index) algorithm provides global terrestrial evapotranspiration information using affordable input data and a simple, fully automated computational procedure. The primary inputs of the algorithm are satellite-observed land surface temperature data and global weather information. The algorithm uses land surface temperature data from the Second-Generation Global Imager (SGLI) onboard the Global Change Observation Mission-Climate satellite as the primary input to provide stable terrestrial evapotranspiration maps with a 250 m spatial resolution. In this study, the algorithm was applied to a 4-year global dataset from 2018‒2021 using a newly developed fully automated procedure. Accuracy assessment of the computational results was conducted using 12 ground-based flux monitoring datasets from AsiaFlux and AmeriFlux networks for 5 land-use categories (cropland, grassland, wetland, broadleaf forest, and needleleaf forest). The evaluation represented an affordable estimation accuracy with almost zero bias, with some random errors expressed as root-mean-squared error = 1.12 (mm day^-1) and coefficient of variation = 0.51. Accuracy was higher for croplands and grasslands than for forests. The estimation accuracy of the algorithm was compared to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 global terrestrial evapotranspiration product. The ET_index algorithm showed a higher overall performance than MOD16, particularly for croplands and grasslands, which may be an advantage of the surface temperature-based approach used in the algorithm. Comparison with the global evapotranspiration product of the Global Land Evaporation Amsterdam Model (GLEAM) confirmed that the global spatial distribution and seasonal variations were consistent, except in some cold regions. The ET_index estimation algorithm and its derived ET products have considerable potential to advance terrestrial sustainability in natural environments, water management, and food production. They support this objective by providing robust and accurate evapotranspiration information.

© Author(s) 2026. Licensed under CC BY 4.0.
Tanada, K. et al., Journal of Agricultural Meteorology, 82(1), 15–30 (2026). https://doi.org/10.2480/agrmet.D-25-00022